1. Field of the Invention
This invention generally relates to computer-implemented methods, carrier media, and systems for selecting polarization settings for an inspection system for inspection of a layer of a wafer. Certain embodiments relate to a computer-implemented method for determining a characteristic of a measure of signal-to-noise for subpopulations of defects, each of which includes defects that are common to at least two different combinations of polarization settings of the inspection system, and selecting the polarization settings for illumination and collection to be used for inspection of a layer of a wafer corresponding to the subpopulation having the best value for the characteristic.
2. Description of the Related Art
The following description and examples are not admitted to be prior art by virtue of their inclusion in this section.
Fabricating semiconductor devices such as logic and memory devices typically includes processing a substrate such as a semiconductor wafer using a large number of semiconductor fabrication processes to form various features and multiple levels of the semiconductor devices. For example, lithography is a semiconductor fabrication process that involves transferring a pattern from a reticle to a resist arranged on a semiconductor wafer. Additional examples of semiconductor fabrication processes include, but are not limited to, chemical-mechanical polishing, etch, deposition, and ion implantation. Multiple semiconductor devices may be fabricated in an arrangement on a single semiconductor wafer and then separated into individual semiconductor devices.
Inspection processes are used at various steps during a semiconductor manufacturing process to detect defects on a specimen such as a reticle and a wafer. Inspection processes have always been an important part of fabricating semiconductor devices such as integrated circuits. However, as the dimensions of semiconductor devices decrease, inspection processes become even more important to the successful manufacture of acceptable semiconductor devices. For instance, as the dimensions of semiconductor devices decrease, detection of defects of decreasing size has become necessary since even relatively small defects may cause unwanted aberrations in the semiconductor devices. Accordingly, much work in the inspection field has been devoted to designing inspection systems that can detect defects having sizes that were previously negligible.
Inspection for many different types of defects has also become more important recently. For instance, in order to use the inspection results to monitor and correct semiconductor fabrication processes, it is often necessary to know what types of defects are present on a specimen. In addition, since controlling every process involved in semiconductor manufacturing is desirable to attain the highest yield possible, it is desirable to have the capability to detect the different types of defects that may result from many different semiconductor processes. The different types of defects that are to be detected may vary dramatically in their characteristics. For example, defects that may be desirable to detect during a semiconductor manufacturing process may include thickness variations, particulate defects, scratches, pattern defects such as missing pattern features or incorrectly sized pattern features, and many others having such disparate characteristics.
Many different types of inspection systems have been developed to detect the different types of defects described above. In addition, most inspection systems are configured to detect multiple different types of defects. In some instances, a system that is configured to detect different types of defects may have adjustable image acquisition and sensitivity parameters such that different parameters can be used to detect different defects or avoid sources of unwanted (nuisance) events. For instance, the spot or pixel size, polarization or the algorithm settings for the angles of collection may be different for an inspection process used to detect particulate defects than for an inspection process used to detect scratches.
Although an inspection system that has adjustable image acquisition and sensitivity parameters presents significant advantages to a semiconductor device manufacturer, these inspection systems are useless if incorrect image acquisition and sensitivity parameters are used for an inspection process. For example, incorrect or non-optimized image acquisition and sensitivity parameters may produce such high levels of noise that no defects can be detected in the generated inspection data. In addition, since the detects, process conditions and noise on a specimen such as a reticle and a wafer may vary dramatically (and since the characteristics of the specimen itself may vary dramatically), the best image acquisition and sensitivity parameters for detecting the defects on a particular specimen may be difficult, if not impossible, to predict. Therefore, although using the correct image acquisition and sensitivity parameters will have a dramatic effect on the results of inspection, it is conceivable that many inspection processes are currently being performed with incorrect or non-optimized image acquisition and sensitivity parameters.
The task of setting up an inspection process for a particular specimen and a particular defect of interest may be extremely difficult for a user particularly when an inspection system has a relatively large number of adjustable image acquisition settings and sensitivity parameters. In addition, it may be impossible to know whether the best inspection process has been found unless all possible combinations of the image acquisition parameters have been tested. However, most inspection processes are currently set up using a large number of manual processes (e.g., manually setting the image acquisition parameters, manually analyzing the resulting inspection data, etc.). As such, setting up the inspection process may take a relatively long time. Furthermore, depending on the types of specimens that will be inspected with the inspection system, a different inspection process may need to be set up for each different type of specimen. Obviously, therefore, setting up the inspection processes for all of the different specimens that are to be inspected may take a prohibitively long time.
Previous methods for selecting one or more polarization settings for an inspection recipe for a process layer are labor intensive processes, which include several iterative steps. The first step of one such method is to perform an inspection scan with predefined default settings for a dark field inspection system. The goal of this step is to locate defects (or anomalies) on the surface of the wafer for the process layer of interest. Of this entire population of defects, the user manually selects a sub-sample of defects to examine further. For each defect, a signal-to-noise ratio is determined (based on the raw image intensities). Basically, this signal-to-noise ratio is a measure of how much more intense the defect scatters relative to its background (or non-defective region). The signal-to-noise for a given defect is strongly dependent on the polarization choice. Therefore, the user must cycle through all of the available polarization options on the dark field inspection system and determine which polarization state will maximize the overall signal-to-noise for this subset of defects.
There are, however, a number of disadvantages to such methods. For example, such methods can be substantially time-consuming and tedious. Depending on the nature of the process layer, the methods described above can take anywhere from a few hours to a few days to find the best polarization setting. In addition, if the user has no prior knowledge of the process layer, the user may choose non-interesting defects in the sub-sample and as a result choose an incorrect polarization setting for the actual defects of interest.
Accordingly, it would be advantageous to develop computer-implemented methods, carrier media, and/or systems for selecting polarization settings for an inspection system for inspection of a layer of a wafer that are less labor intensive, quicker, and less tedious than previously used methods and that result in polarization setting selections that are more appropriates or even optimal, for inspection of a layer on a wafer than polarization settings selected using the methods described above.